Main > Laser & Optoelectronics Progress >  Volume 57 >  Issue 20 >  Page 201020 > Article
  • Abstract
  • Abstract
  • View Summary
  • Figures (9)
  • Tables (3)
  • Equations (0)
  • References (15)
  • Get PDF(in Chinese)
  • Paper Information
  • Received: Jan. 13, 2020

    Accepted: Feb. 24, 2020

    Posted: Oct. 1, 2020

    Published Online: Oct. 17, 2020

    The Author Email: Chen Yong (edukeylab@126.com)

    DOI: 10.3788/LOP57.201020

  • Get Citation
  • Copy Citation Text

    Yong Chen, Jin Chen, Yapeng Ai, Meifeng Tao. Dunhuang Mural Inpainting Algorithm Based on Sequential Similarity Detection and Cuckoo Optimization[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201020

    Download Citation

  • Category
  • Image Processing
  • Share
Laser & Optoelectronics Progress, Vol. 57, Issue 20, 201020 (2020)

Dunhuang Mural Inpainting Algorithm Based on Sequential Similarity Detection and Cuckoo Optimization

Chen Yong*, Chen Jin, Ai Yapeng, and Tao Meifeng

Author Affiliations

  • School of Electronics and Information Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China

Abstract

In this paper, we proposed the Dunhuang inpainting mural restoration algorithm based on the combination of sequential similarity detection algorithm and cuckoo search algorithm to improve the incorrect filling problem of the Criminisi algorithm and low efficiency in Dunhuang murals restoration. First, we improved the priority calculation formula with the method of redefining data items using a P-Laplace operator to eradicate the priority calculation tends to zero. Second, we improved the efficiency of mural restoration using the sequential similarity detection algorithm based on the dynamic threshold for searching matching blocks. To make the matching block more reasonable, we used a cuckoo optimization algorithm to determine the best matching block. Finally, mural restoration was completed through iterative updates. The results of restoration experiments on Dunhuang mural inpainting show that compared with similar comparison algorithms, the proposed algorithm in this paper achieves better subjective and objective restoration effects, and improves the restoration efficiency.

keywords

Please Enter Your Email: